Sunday, February 15, 2015

Testing for Multivariate Normality

The assumption that multivariate data are (multivariate) normally distributed is central to many statistical techniques. The need to test the validity of this assumption is of paramount importance, and a number of tests are available.

A recently released R package, MVN, by Korkmaz et al. (2014) brings together several of these procedures in a friendly and accessible way. Included are the tests proposed by Mardia, Henze-Zirkler, and Royston, as well as a number of useful graphical procedures.

If for some inexplicable reason you're not a user of R, the authors have thoughtfully created a web-based application just for you!


Korkmaz, S., D. Goksuluk, and G. Zarasiz
, 2014. An R package for assessing multivariate normality. The R Journal, 6/2, 151-162.

© 2015, David E. Giles

New Canadian Provincial Data

I was delighted to see the release, last week, of a new Statistics Canada research paper, "Provincial Convergence and Divergence in Canada, 1926 to 2011". Co-authored by W. Mark Brown and (UVic grad.) Ryan McDonald.

It's a very interesting paper that makes use of some equally interesting new data that Statistics Canada has released recently. For once, Statistics Canada has gone to considerable efforts to assemble a really useful long-run data-set (see Cansim Table 384-5000 This is a far cry from the myriad of "Series Discontinued" flags that we're used to seeing in the Cansim database, and it's great to see that Ryan has been instrumental in its development (McDonald, 2015).

As he notes, "More advanced statistical methods, and models with greater breadth and depth, are difficult to apply to existing fragmented Canadian data. The longitudinal nature of the new provincial dataset remedies this shortcoming."

Data is an econometrician's life-blood. We need to see more of this from Statistics Canada.


McDonald, R., 2015. Constructing Provincial Time Series: A Discussion of Data Sources and Methods. Income and Expenditure Accounts Technical Series, no. 77 Statistics Canada Catalogue no. 13-604-M. Ottawa: Statistics Canada.

© 2015, David E. Giles